def count_steps(data):
print 'count_steps'
plot_data(data)
mag = vector_magnitude(data)
plot_mag(mag)
average = moving_average(data, 100)
plot_mag(average)
num_steps = 0
'''
This function counts the number of steps in data and returns the number of steps
'''
i = 0
found = False
stepArray = []
for x in average:
if (x >= 4 and x <= 4.03):
if found == False:
num_steps = num_steps + 1
stepArray.append(i)
found = True
else:
found = False
i = i + 1
plot_steps(average, stepArray)
return num_steps
def sum_sensors(self, prey_list, predator_list):
vectors = []
cohesion_vector = self.cohesion_vector(prey_list)
vectors.append(util.multiply_vector(cohesion_vector, self.COHESION_WEIGHT))
follow_vector = self.follow_vector(prey_list)
vectors.append(util.multiply_vector(follow_vector, self.FOLLOW_WEIGHT))
separation_vector = self.separation_vector(prey_list)
vectors.append(util.multiply_vector(separation_vector, self.SEPARATION_WEIGHT))
predator_vector = self.predator_vector(predator_list)
vectors.append(util.multiply_vector(predator_vector, self.PREDATOR_WEIGHT))
vectors.append(self.edge_repulsion_sensor())
x_comp = 0
y_comp = 0
for x, y in vectors:
x_comp += x
y_comp += y
vector_magnitude = util.vector_magnitude((x_comp, y_comp))
if vector_magnitude > self.MAX_SPEED:
x_comp /= vector_magnitude
y_comp /= vector_magnitude
x_comp *= self.MAX_SPEED
y_comp *= self.MAX_SPEED
return (x_comp, y_comp)
def sum_sensors(self, prey_list, predator_list):
vectors = []
prey_pos_vector = self.get_closest_prey_position(prey_list)
vectors.append(util.multiply_vector(prey_pos_vector, self.PREY_POS_WEIGHT))
prey_vel_vector = self.get_closest_prey_velocity(prey_list)
vectors.append(util.multiply_vector(prey_vel_vector, self.PREY_VEL_WEIGHT))
vectors.append(util.multiply_vector(self.edge_repulsion_sensor(), 100))
print vectors
print """Prey_Pos: {}
Prey_Vel: {}
Repulsion: {}""".format(*vectors)
x_comp = 0
y_comp = 0
for x, y in vectors:
x_comp += x
y_comp += y
vector_magnitude = util.vector_magnitude((x_comp, y_comp))
if vector_magnitude > self.MAX_SPEED:
x_comp /= vector_magnitude
y_comp /= vector_magnitude
x_comp *= self.MAX_SPEED
y_comp *= self.MAX_SPEED
return (x_comp, y_comp)
def count_steps(data):
print 'count_steps'
# Different Algo
num_steps = 0
plot_data(data)
plot_mag(vector_magnitude(data))
plot_mag(moving_average((data),230))
'''
This function counts the number of steps in data and returns the number of steps
'''
return num_steps
def run():
# Get data
file_name = "data.txt" # Change to your file name
data = iosParser.get_data(file_name)
# print data
number_of_steps = count_steps(data)
magnitudes = util.vector_magnitude(data)
plot_mag(magnitudes)
moving_avg = util.moving_average(magnitudes, 10)
plot_mag(moving_avg)
print "Number of steps counted are :", number_of_steps
def count_steps(data):
print "Accelerometer data graph"
plot_data(data)
mag = vector_magnitude(data)
plot_mag(mag)
average = moving_average(data, 10)
plot_mag(average)
num_steps = 0
'''
ADD YOUR CODE HERE. This function counts the number of steps in data and returns the number of steps
'''
return num_steps
def sum_sensors(self, prey_list, predator_list):
vectors = []
prey_pos_vector = self.get_closest_prey_position(prey_list)
vectors.append(
util.multiply_vector(prey_pos_vector, self.PREY_POS_WEIGHT))
prey_vel_vector = self.get_closest_prey_velocity(prey_list)
vectors.append(
util.multiply_vector(prey_vel_vector, self.PREY_VEL_WEIGHT))
vectors.append(util.multiply_vector(self.edge_repulsion_sensor(), 100))
print vectors
print """Prey_Pos: {}
Prey_Vel: {}
Repulsion: {}""".format(*vectors)
x_comp = 0
y_comp = 0
for x, y in vectors:
x_comp += x
y_comp += y
vector_magnitude = util.vector_magnitude((x_comp, y_comp))
if vector_magnitude > self.MAX_SPEED:
x_comp /= vector_magnitude
y_comp /= vector_magnitude
x_comp *= self.MAX_SPEED
y_comp *= self.MAX_SPEED
return (x_comp, y_comp)